Childhood pegboard task predicts adult-onset psychosis-spectrum disorder among a genetic high-risk sample

Research output: Contribution to journalJournal articleResearchpeer-review

  • Pamela Rakhshan
  • Holger Jelling Sørensen
  • Jordan DeVylder
  • Vijay Mittal
  • Mortensen, Erik Lykke
  • Niels M Michelsen
  • Morten Ekstrøm
  • Steven C Pitts
  • Sarnoff A Mednick
  • Jason Schiffman

Motor abnormalities have been established as a core aspect of psychosis-spectrum disorders, with numerous studies identifying deficits prior to clinical symptom presentation. Additional research is needed to pinpoint standardized motor assessments associated with psychosis-spectrum disorders prior to illness onset to enhance prediction and understanding of etiology. With a long history of findings among people with diagnosable psychosis-spectrum disorders, but little research conducted during the premorbid phase, pegboard tasks are a viable and understudied measure of premorbid for psychosis motor functioning. In the current study, examining data from the Copenhagen Perinatal Cohort, the Simultaneous Pegs Test was performed with children (n=244, aged 10-13) at genetic high risk for psychosis (n=94) and controls (n=150). Findings suggest that children who eventually developed a psychosis-spectrum disorder (n=33) were less likely to successfully complete the task within time limit relative to controls (χ(2)(2, N=244)=6.94, p=0.03, ϕ=0.17). Additionally, children who eventually developed a psychosis-spectrum disorder took significantly longer to complete the task relative to controls (χ(2)(2, N=244)=7.06, p=0.03, ϕ=0.17). As pegboard performance is thought to tap both diffuse and specific brain networks, findings suggest that pegboard tests may be useful premorbid measures of motor functioning among those on a trajectory towards a psychosis-spectrum disorder.

Original languageEnglish
JournalSchizophrenia Research
Volume178
Issue number1-3
Pages (from-to)68-73
Number of pages6
ISSN0920-9964
DOIs
Publication statusPublished - Dec 2016

ID: 177525151